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Relaxation and single site multiple mutations to identify and control allosteric networks.
- Source :
-
Methods . Aug2023, Vol. 216, p51-57. 7p. - Publication Year :
- 2023
-
Abstract
- • Relaxation And Single Site Multiple Mutations (RASSMM) is an approach that combines mutagenesis, NMR, and functional assays. • RASSMM utilizes findings that indicate each mutation at a single site imparts different changes to both allosteric networks and functions. • Using various mutations, RASSMM matches network changes to functional outcomes, revealing each network's role. Advances in Nuclear Magnetic Resonance (NMR) spectroscopy have allowed for the identification and characterization of movements in enzymes over the last 20 years that has also revealed the complexities of allosteric coupling. For example, many of the inherent movements of enzymes, and proteins in general, have been shown to be highly localized but nonetheless still coupled over long distances. Such partial couplings provide challenges to both identifying allosteric networks of dynamic communication and determining their roles in catalytic function. We have developed an approach to help identify and engineer enzyme function, called Relaxation And Single Site Multiple Mutations (RASSMM). This approach is a powerful extension of mutagenesis and NMR that is based on the observation that multiple mutations to a single site distal to the active site allosterically induces different effects to networks. Such an approach generates a panel of mutations that can also be subjected to functional studies in order to match catalytic effects with changes to coupled networks. In this review, the RASSMM approach is briefly outlined together with two applications that include cyclophilin-A and Biliverdin Reductase B. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10462023
- Volume :
- 216
- Database :
- Academic Search Index
- Journal :
- Methods
- Publication Type :
- Academic Journal
- Accession number :
- 164583553
- Full Text :
- https://doi.org/10.1016/j.ymeth.2023.06.002